Data Science with Python for SEO

4.5

(8 ratings)

·

5 Days

·

Cohort-based Course

2024: "I don't need Python to do SEO, I use Excel.” 1994: "I don't need Excel to do accounting, I use a calculator."

Course overview

Start analyzing larger data in bulk with automated processes – for beginners.

As a professional data practitioner, the ideal scenario is your ability to handle raw data with the full flexibility of a programming language. Opening files, analyzing data, creating simple charts, and automating some basic tasks are some of the outcomes you will leave with.


You will also be exploring how to use some of the most important packages for data and SEO work.

Who is this course for

01

SEOs who have a lot of data to handle, want to get insights, and really love digging into data.

02

Search marketers who want to be on top of their data, and provide interesting insights that the typical tools cannot provide.

03

Opinionated data analysts who want the complete freedom to dig in to any dataset they want without any tool restrictions.

What you’ll get out of this course

Take your data work to a new level

Easy-to-use "point and click" tools are very convenient and quick. Usually, this convenience comes with restrictions and limitations.


We will take the first steps into starting to work with raw data and utilizing the full flexibility of a programming language - Python.

Start to think programmatically and in bulk

Many toy tools help you with analyzing a single page or a URL, but you really need to establish the ability to do everything in bulk.


You will see examples of that, and will be pointed to tools in that direction.

Think Implementation

Remember that moment after reading a great article when you felt really excited about new opportunities?


You probably felt stuck, because you weren't sure how to do that on a website with 72,345 URLs.


Data Science skills allow you to implement whatever you want with your data.

Think analytics and diagnosis

Remember that moment after reading a great article: Part 2.


Yes, but what is the current situation compared to the ideal one?


Do you know how to assess a business/website with 72,345 URLs?


Data Science skill can help in that.

Data visualization - a chart is worth a thousand words!

We will start with very basic chart types and see how to programmatically build them with various options.


You first need to "see" your data.

This course includes

3 interactive live sessions

Lifetime access to course materials

11 in-depth lessons

Direct access to instructor

Projects to apply learnings

Guided feedback & reflection

Private community of peers

Course certificate upon completion

Maven Satisfaction Guarantee

This course is backed by Maven’s guarantee. You can receive a full refund within 14 days after the course ends, provided you meet the completion criteria in our refund policy.

Course syllabus

Expand all modules
  • Week 1

    Mar 4—Mar 8

    Week dates are set to instructor's time zone

    Events

    • Mar

      4

      Session 1

      Mon, Mar 4, 2:00 PM - 4:00 PM UTC

    • Mar

      6

      Session 2

      Wed, Mar 6, 2:00 PM - 4:00 PM UTC

    • Mar

      8

      Session 3

      Fri, Mar 8, 2:00 PM - 4:00 PM UTC

    Modules

    • Free preview

      Session 1

    • Free preview

      Session 2

    • Free preview

      Session 3

    • Free preview

      Session 4 (bonus)

4.5

(8 ratings)

What students are saying

Meet your instructor

Elias Dabbas

Elias Dabbas

Creator of advertools

Having always worked with data (making decisions and responsible for their outcomes), I have been obsessively exploring various Data Science topics in the last decade.


I found a gap in packages for the SEO/SEM practitioner, and decided to create one. You will learn a lot about it in the course, and explore how you can use it in your daily work, and even contribute to it. Did I mention that it's open-source and free?


Understanding data is both an abstract, as well as an intuitive activity for me, so I love to visualize my data, refine my charts, until they speak for themselves. So I also authored a book on how to build interactive dashboards and data apps with Plotly's Dash.

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Course schedule

6 Hours (in one week)
  • Monday, Wednesday, and Friday

    Two hours each day 14:00 - 16:00 GMT

    Designed to fit in your regular schedule, and to allow you time in between, to practice and absorb the topics discussed.

  • Homework

    Optional extra stuff

    You'll be given many additional resources, notebooks, and scripts to explore and try on your own.

Free resource

advertools office hours

Thursday 16:00 CEST (Berlin, Rome, Vienna)


FREE

Live coding

You will also be coding, creating charts, sharing your work, and giving feedback if you want.

You will get:

  1. Zoom meeting link
  2. An optional link to register for a Python environment if you want to code along
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Learning is better with cohorts

Learning is better with cohorts

Active hands-on learning

We will be analyzing data and coding together throughout the course.

Work in groups

Just like at work, you will get a chance to review other people's work, provide feedback, and get it for your work.

Showcase your work and build your data portfolio

Start sharing and showcasing your work right from the beginning, and establish yourself as an authority on the topic(s) that you love.

Frequently Asked Questions

What happens if I can’t make a live session?
I work full-time, what is the expected time commitment?
What’s the refund policy?
I have never programmed before, is this course for me?

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